The seemingly omnipresent Malcolm Gladwell in the New Yorker profiles a new book that is adding to the trend of statisticians applying their techniques to questions surrounding sports. This movement is most famous in baseball where sabermetrics is an accepted part of the game's firmament.
This new book, "The Wages of Wins" by David J. Berri, Martin B. Schmidt, and Stacey L. Brook applies statistical techniques to a whole host of sports questions. They find that many traditional sports truisms are indeed false. (The authors also have a blog in which they address some of the issues raised in the Gladwell piece on the NBA.)
The theme of the Gladwell piece is that in many situations, like basketball, it is difficult to identify the "true" variables underlying success. Even a casual fan of basketball must acknowledge that there is more to basketball than scoring, but our eyes often fail us. We focus on those factors that are more readily available and that are reinforced by the highlights driven media.
The problem for basketball experts is that, in a situation with many variables, it’s difficult to know how much weight to assign to each variable. Buying a house is agonizing because we look at the size, the location, the back yard, the proximity to local schools, the price, and so on, and we’re unsure which of those things matters most. Assessing heart-attack risk is a notoriously difficult task for similar reasons. A doctor can analyze a dozen different factors. But how much weight should be given to a patient’s cholesterol level relative to his blood pressure? In the face of such complexity, people construct their own arbitrary algorithms—they assume that every factor is of equal importance, or randomly elevate one or two factors for the sake of simplifying matters—and we make mistakes because those arbitrary algorithms are, well, arbitrary.
Arbitrary algorithms is a good description of the way many investors go about identifying trades. Frankly, many are lucky if that have an alogorithm beyond the "seat of their pants." While that may work for some from time to time that is not a durable, long term strategy.
Long term investment success is ultimately driven by embracing greater rigor in one's investment process. Some investors were able to acquire this over time and through (costly) trial and error. In this day and age however the introduction of cheap data and even cheaper computing power frees us up to explore financial data in ways unimaginable only a decade ago.
We would encourage readers to seek out resources that help illuminate the markets through rigorous methods. For those with a shorter-term time frame Brett Steenbarger publishes interesting studies on price reactions in the equity markets. For those with a more academic bent, the CXO Advisory Group regularly summarizes recent academic research that is relevant to investing and trading. We would love to hear from any readers who have identified other sites with this sort of bent.
The bottom line is that arbitrary algorithms in investing, as in sports, will most likely lead to arbitrary results. Informed investors seeking out consistent success need to approach the markets with some rigor and not fear a little hypothesis testing.
